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Fast-convergence algorithm for ICA-based blind source separation using array signal processing

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3 Author(s)
Saruwatari, H. ; Graduate Sch. of Inf. Sci., Nara Inst. of Sci. & Technol., Japan ; Kawamura, Toshiya ; Shikano, K.

We propose a new algorithm for blind source separation (BSS), in which independent component analysis (ICA) and beamforming are combined to resolve the low-convergence problem through optimization in ICA. The proposed method consists of the following two parts: frequency-domain ICA with direction-of-arrival (DOA) estimation, and null beamforming based on the estimated DOA. The alternation of learning between ICA and beamforming can realize fast- and high-convergence optimization. The results of the signal separation experiments reveal that the signal separation performance of the proposed algorithm is superior to that of the conventional ICA-based BSS method

Published in:

Statistical Signal Processing, 2001. Proceedings of the 11th IEEE Signal Processing Workshop on

Date of Conference:

2001